From a Dead Account to a $80K+ Sales Engine: Building a Predictable Google Ads Quote Machine for Math4Sale

Client Overview

Math4Sale is a B2B e-commerce business that has spent 20 years as one of the country's go-to sources for graphing calculators, supplying schools and districts with bulk classroom sets of Texas Instruments models like the TI-84 Plus and TI-84 Plus CE. They'd already built a serious operation — doing close to eight figures a year on Amazon, with a dialed-in quote-and-close process running on Shopify and Pipedrive and a 20-year reputation behind them.

The goal was to build a direct-to-buyer channel that didn't depend on Amazon. Math4Sale wanted a predictable inbound engine on Google that would put qualified quote requests from school buyers in front of their sales team, so they could sell more of their in-house inventory at full margin. Their target was straightforward: 5 to 10 quote requests a week, roughly $40,000 in new pipeline each week, and a path to scale toward $2–3M in direct sales.

The Challenge

Math4Sale had never run Google Ads successfully before. A previous freelancer had set up the account but, in the client's words, didn't know what they were doing — and it showed. When we got in, the existing campaigns weren't spending at all: zero impressions across the board, even with broad-match keywords and a PMax campaign live. Something was broken at the account level, not the strategy level.

On top of the delivery problem, this was a fundamentally tricky account to run well:

It's not traditional e-commerce

Sales don't happen on the website. A buyer requests a quote, the sales team follows up, and the deal closes offline days or weeks later. Optimizing this like a standard Shopify store would have been the wrong playbook entirely.

Single units are a trap

Math4Sale only makes real margin on bulk 10-packs and classroom sets. Every dollar spent capturing someone shopping for a single calculator is a dollar wasted competing against Amazon and eBay. Keeping traffic on bulk and institutional intent — and off singles, scientifics, and off-brand models — was a constant discipline.

Attribution was hard by design

With a high average order value, a long and variable sales cycle, and the real revenue landing in the CRM rather than the cart, Google had no visibility into which clicks actually turned into money. Without solving that, we'd be optimizing blind.

What We Did

1. Rebuilt the account from a clean slate. Rather than fight the broken legacy account and its PMax setup, we wiped the old campaigns and rebuilt the structure around what this business actually needed: a focused Search program targeting bulk and school-specific intent, backed by a keyword plan and forecast we reviewed with the client before launch. New campaigns were live within days of kickoff, and the account started spending and converting almost immediately.

2. Engineered offline conversion tracking so Google could optimize on real revenue. This was the real unlock. Because closed deals live in Pipedrive, not Shopify's checkout, we built a full closed-loop attribution system: GCLID capture on every quote and contact form via GTM, passed into Pipedrive on each lead, then wired through n8n so that when a deal is marked Won, the actual deal value fires back to Google Ads as an offline conversion. That means the algorithm stopped optimizing toward raw form-fills and started optimizing toward the keywords and searches that produce real closed revenue.

3. Kept the traffic on high-margin intent. We ran an ongoing discipline of search-term review, negative-keyword additions, and budget shifts toward the terms producing quality quotes — while deliberately not over-pruning. Generic and off-target searches (scientific calculators, competitor-only models, vague "cost savings" terms) got excluded; genuine bulk and classroom-set intent stayed in. When broader terms showed potential, we tightened the ad messaging (10-pack language, classroom/school intent, clear pricing, multi-pack imagery) to pre-qualify the click before spending on it.

4. Scaled spend as the signal proved out, and managed the seasonality. As quotes and closes came in, we ramped budgets in step with performance, moving from an initial daily budget up to $300/day across the core campaigns as results justified it. We also planned around the buying calendar — pulling back during the summer school-break lull and preparing to ramp aggressively into the new-budget season — so spend followed demand instead of fighting it.

The Results

The account went from spending nothing and converting nothing to a live, revenue-generating engine — fast. Within the first several weeks of the rebuilt program, Math4Sale reported:

• $66,499 in closed sales attributed to the ads program shortly after launch, climbing to $80,000+ closed with $223,000+ in active pipeline by the end of May

• A representative month of ~$11,000 in ad spend producing ~$50,000 in closed sales — the client describing roughly a 2.5x return on spend in profit terms, and materially higher on revenue

• Quote requests landing in the exact 5–10-per-week range the client set as their 90-day success target, including multiple $10,000–$30,000+ opportunities entering the pipeline

Because Math4Sale's customer lifetime value runs $20,000+ over a multi-year relationship, leads acquired at a few hundred dollars each make the long-term return math extremely favorable — and that's before the compounding value of winning a school or district as a repeat institutional buyer.

Key Outcomes

• Took a completely non-delivering Google Ads account (zero impressions) to a live, converting revenue engine within days of rebuild

• Generated $80K+ in closed sales and $223K+ in pipeline in the opening months of the program

• Delivered the client's target of 5–10 qualified quote requests per week

• Built closed-loop offline conversion tracking (GCLID → Pipedrive → n8n → Google Ads) so bidding optimizes on real closed revenue, not just leads

• Held traffic on high-margin bulk and classroom intent, protecting margin by keeping spend off single-unit searches

• Scaled daily budget in step with proven performance while managing the school-year seasonality

The Bottom Line

Math4Sale had a great business with a broken front door: an eight-figure operation, a dialed-in sales process, and a Google Ads account that literally wasn't running. We rebuilt the account around how the business actually makes money — high-margin bulk quotes closing offline — and then solved the hard part almost nobody bothers with in B2B: feeding real closed-deal revenue back into Google so the platform optimizes toward dollars, not form-fills. The result was a predictable quote engine producing $80K+ in closed sales and a six-figure pipeline in its first months, on a channel that had previously produced nothing. The playbook was the same as always: fix the foundation, track what actually matters, protect the margin, and scale what works.